June 3, 2020
Policymakers in different Countries have introduced different political action to contrast the COVID19 contagion.
What are the different containment efforts and is there a strategies resemblance across countries?
What is the effect of these policies on the contagion from a global perspective?
Has the same action lead to different results in the case of different regions of Italy?
COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University for contagion data,
Oxford COVID-19 Government Response Tracker (OxCGRT) for policies tracking.
Dimension Reduction via Polychoric PCA for \(11\) ordinal variables (from \(0\) to \(2\) or \(0\) to \(3\)) indicating the stringency level of policies such as
School, workplace and transport closing and event cancellation;
Gathering, stay-home and internal/international movement restrictions;
Information, Testing and Contact Tracing campaigns.
Functional Data Co-Clustering of the countries aligned to the first contagion (from the 10th day before contagion).
Restriction-based policies on one hand, Tracing and Testing policies on the other hand.
WHY?
We analyze the number of Active person, i.e., Confirmed - Deaths - Recovered, \(14\) days after lockdown policies application\(\rightarrow\) Count Dependent Variable (Generalized Poisson Model);
The data are observed for each country nested within clusters during \(131\) days \(\rightarrow\) Mixed Model.
Lockdown policies work! respect to impose no measure;
Strong Testing and Tracing policies lead to discovering more infected people (luckily!)
Korea and Singapore are the best countries that acted properly;
Sweden, Germany, Portugal, and Greece better than the other UE countries;
The USA, and Canada better than the other UE countries except for Sweden and Germany.
Italian regions, ethernal divide
Lockdown almost simultaneous, excepted the Red Zone
First cases in Lombardia and Lazio hubs
Policies have no variability between regions
Baseline control: some regions start from worse situations
Cannot estimates some effects as for the nations case
To our defense, integration between databases came lately
Instrumental variables, more correct but tricky approach
Phase “1” versus Phase “0” comparison
Random effects for region and date, standard panel approach
Assuming policies effects seen ~14 days later
Controlling for testing frequency